Book Image

Introduction to R for Business Intelligence

By : Jay Gendron
Book Image

Introduction to R for Business Intelligence

By: Jay Gendron

Overview of this book

Explore the world of Business Intelligence through the eyes of an analyst working in a successful and growing company. Learn R through use cases supporting different functions within that company. This book provides data-driven and analytically focused approaches to help you answer questions in operations, marketing, and finance. In Part 1, you will learn about extracting data from different sources, cleaning that data, and exploring its structure. In Part 2, you will explore predictive models and cluster analysis for Business Intelligence and analyze financial times series. Finally, in Part 3, you will learn to communicate results with sharp visualizations and interactive, web-based dashboards. After completing the use cases, you will be able to work with business data in the R programming environment and realize how data science helps make informed decisions and develops business strategy. Along the way, you will find helpful tips about R and Business Intelligence.
Table of Contents (19 chapters)
Introduction to R for Business Intelligence
About the Author
About the Reviewers
R Packages Used in the Book
R Code for Supporting Market Segment Business Case Calculations

Analyzing two variables together

If your dataset has two variables, you have bivariate data. When examining bivariate data, you want to explore possible relationships. This is where good questioning pays off. You can use the following four questions to guide your exploratory data analysis:

  • What does the data look like?

  • Is there any relationship between two variables?

  • Is there any correlation between the two?

  • Is the correlation significant?

Four words summarize these questions: Look-Relationships-Correlation-Significance. You will explore pairs of variables from the marketing dataset to investigate these questions using both tabular and graphical exploration methods.

What does the data look like?

This is something you know very well at this point. Summarize the data in your console as shown in the following:


The following is the output:

google_adwords      facebook        twitter       marketing_total 
 Min.   : 23.65   Min.   : 8.00   Min.   :  5.89   Min.   : 53.65